Computer-readable recording medium storing arithmetic program, arithmetic method, and information processing device

Abstract

A non-transitory computer-readable recording medium storing an arithmetic program for causing a computer to repeatedly execute processing including: creating a plurality of Ising models by creating the Ising models for each of a plurality of characteristic values, based on a training data group that includes a plurality of pieces of training data in which data and the plurality of characteristic values for the data are associated with each other; creating a combined Ising model by combining the plurality of Ising models; searching for the data of a recommended point for the combined Ising model; and adding, to the training data group, the training data that includes the data of the recommended point and the plurality of characteristic values for the data of the recommended point.

What is claimed is: 
     
         1 . A non-transitory computer-readable recording medium storing an arithmetic program for causing a computer to repeatedly execute processing comprising:
 creating a plurality of Ising models by creating the Ising models for each of a plurality of characteristic values, based on a training data group that includes a plurality of pieces of training data in which data and the plurality of characteristic values for the data are associated with each other;   creating a combined Ising model by combining the plurality of Ising models;   searching for the data of a recommended point for the combined Ising model; and   adding, to the training data group, the training data that includes the data of the recommended point and the plurality of characteristic values for the data of the recommended point.   
     
     
         2 . The non-transitory computer-readable recording medium according to  claim 1 , the processing further comprising:
 creating the combined Ising model by weighting each of the plurality of Ising models and adding each of the plurality of Ising models together.   
     
     
         3 . The non-transitory computer-readable recording medium according to  claim 2 , the processing further comprising:
 correcting the weights according to the plurality of characteristic values.   
     
     
         4 . The non-transitory computer-readable recording medium according to  claim 1 , wherein, in a case where the recommended point retrieved in the search is already included in the training data group,
 the combined Ising model is recreated when the plurality of Ising models used to search for the recommended point is combined, and   the recommended point is searched for, for the recreated combined Ising model.   
     
     
         5 . The non-transitory computer-readable recording medium according to  claim 1 , wherein the data is vector data with a binary value. 
     
     
         6 . An arithmetic method implemented by a computer, comprising:
 creating a plurality of Ising models by creating the Ising models for each of a plurality of characteristic values, based on a training data group that includes a plurality of pieces of training data in which data and the plurality of characteristic values for the data are associated with each other;   creating a combined Ising model by combining the plurality of Ising models;   searching for the data of a recommended point for the combined Ising model; and   adding, to the training data group, the training data that includes the data of the recommended point and the plurality of characteristic values for the data of the recommended point, wherein   the creating of the plurality of Ising models, the creating of the combined Ising model, the searching for the data of the recommended point, and the adding of the training data are repeatedly executed by the computer.   
     
     
         7 . An information processing apparatus comprising:
 a memory; and   a processor coupled to the memory, the processor being configured to repeatedly perform processing including:   creating a plurality of Ising models by creating the Ising models for each of a plurality of characteristic values, based on a training data group that includes a plurality of pieces of training data in which data and the plurality of characteristic values for the data are associated with each other;   creating a combined Ising model by combining the plurality of Ising models;   searching for the data of a recommended point for the combined Ising model; and   updating the training data group by adding, to the training data group, the training data that includes the data of the recommended point and the plurality of characteristic values for the data of the recommended point.